Academic writing support : empowering undergraduates' academic writing / Siti Ruqayyah As-Sadiq Abdul Rahim

Academic writing skills needs differ from one discipline to another. This is reflected in the nature of academic writing of the discipline, the academic writing challenges writers face and the resources that are available. In seeking to develop an empowered writer, the right provision of support should be made available according to the needs of the writer. This study investigates the academic writing needs and the academic writing support needs of undergraduates from three various discipline (TESL, Art and Science) of one faculty of Education at a public university in Malaysia. This is the only university with a language policy where English is the medium of teaching and learning. This study applies the mix method design of Plowright (2011), the Frameworks for an Integrated Methodology (FRalM). This study reports the findings of numerical data analysis generated from third year undergraduate students (n=196) and narrative data analysis from both academicians (n=4) and students (n=8). Findings indicated that there is an absence of academic writing support. The findings inform that although all three program disciplines are under the same faculty, their academic writing needs are distinctively different. This study proposes that an academic writing support in the form of a writing centre would be able to facilitate the varying academic writing needs of undergraduates in the faculty

An improved dandelion optimizer algorithm for spam detection next-generation email filtering system

Spam emails have become a pervasive issue in recent years, as internet users receive increasing amounts of unwanted or fake emails. To combat this issue, automatic spam detection methods have been proposed, which aim to classify emails into spam and non-spam categories. Machine learning techniques have been utilized for this task with considerable success. In this paper, we introduce a novel approach to spam email detection by presenting significant advancements to the Dandelion Optimizer (DO) algorithm. DO is a relatively new nature-inspired optimization algorithm inspired by the flight of dandelion seeds. While DO shows promise, it faces challenges, especially in high-dimensional problems such as feature selection for spam detection. Our primary contributions focus on enhancing the DO algorithm. Firstly, we introduce a new local search algorithm based on flipping (LSAF), designed to improve DO's ability to find the best solutions. Secondly, we propose a reduction equation that streamlines the population size during algorithm execution, reducing computational complexity. To showcase the effectiveness of our modified DO algorithm, which we refer to as Improved DO (IDO), we conduct a comprehensive evaluation using the Spam base dataset from the UCI repository. However, we emphasize that our primary objective is to advance the DO algorithm, with spam email detection serving as a case study application. Comparative analysis against several popular algorithms, including Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Generalized Normal Distribution Optimization (GNDO), Chimp Optimization Algorithm (ChOA), Grasshopper Optimization Algorithm (GOA), Ant Lion Optimizer (ALO), and Dragonfly Algorithm (DA), demonstrates the superior performance of our proposed IDO algorithm. It excels in accuracy, fitness, and the number of selected features, among other metrics. Our results clearly indicate that IDO overcomes the local optima problem commonly associated with the standard DO algorithm, owing to the incorporation of LSAF and the reduction equation methods. In summary, our paper underscores the significant advancement made in the form of the IDO al-gorithm, which represents a promising approach for solving high-dimensional optimization prob-lems, with a keen focus on practical applications in real-world systems. While we employ spam email detection as a case study, our primary contribution lies in the improved DO algorithm, which is efficient, accurate, and outperforms several state-of-the-art algorithms in various metrics. This work opens avenues for enhancing optimization techniques and their applications in machine learning

Securing mobile edge computing using hybrid deep learning method

In recent years, Mobile Edge Computing (MEC) has revolutionized the landscape of the telecommunication industry by offering low-latency, high-bandwidth, and real-time processing. With this advancement comes a broad range of security challenges, the most prominent of which is Distributed Denial of Service (DDoS) attacks, which threaten the availability and performance of MEC’s services. In most cases, Intrusion Detection Systems (IDSs), a security tool that monitors networks and systems for suspicious activity and notify administrators in real time of potential cyber threats, have relied on shallow Machine Learning (ML) models that are limited in their abilities to identify and mitigate DDoS attacks. This article highlights the drawbacks of current IDS solutions, primarily their reliance on shallow ML techniques, and proposes a novel hybrid Autoencoder–Multi-Layer Perceptron (AE–MLP) model for intrusion detection as a solution against DDoS attacks in the MEC environment. The proposed hybrid AE–MLP model leverages autoencoders’ feature extraction capabilities to capture intricate patterns and anomalies within network traffic data. This extracted knowledge is then fed into a Multi-Layer Perceptron (MLP) network, enabling deep learning techniques to further analyze and classify potential threats. By integrating both AE and MLP, the hybrid model achieves higher accuracy and robustness in identifying DDoS attacks while minimizing false positives. As a result of extensive experiments using the recently released NF-UQ-NIDS-V2 dataset, which contains a wide range of DDoS attacks, our results demonstrate that the proposed hybrid AE–MLP model achieves a high accuracy of 99.98%. Based on the results, the hybrid approach performs better than several similar techniques

Advances on Network Protocols and Algorithms for Vehicular Ad Hoc Networks

Vehicular Ad Hoc Network (VANET) is an emerging area of wireless ad hoc networks that facilitates ubiquitous connectivity between smart vehicles through Vehicle-to-Vehicle (V2V) or Vehicle-to-Roadside (V2R) and Roadside-to- Vehicle (R2V) communications. This emerging field of technology aims to improve safety of passengers and traffic flow, reduces pollution to the environment and enables in-vehicle entertainment applications. The safety-related applications could reduce accidents by providing drivers with traffic information such as collision avoidances, traffic flow alarms and road surface conditions. Moreover, the passengers could exploit an available infrastructure in order to connect to the internet for infomobility and entertainment applications.Lloret, J.; Ghafoor, KZ.; Rawat, DB.; Xia, F. (2013). Advances on Network Protocols and Algorithms for Vehicular Ad Hoc Networks. Mobile Networks and Applications. 18(6):749-754. doi:10.1007/s11036-013-0490-7S749754186Lloret J, Canovas A, Catalá A, Garcia M (2013) Group-based protocol and mobility model for VANETs to offer internet access. J Netw Comput Appl 36(3):1027–1038. doi: 10.1016/j.jnca.2012.02.009Khokhar RH, Zia T, Ghafoor KZ, Lloret J, Shiraz M (2013) Realistic and efficient radio propagation model for V2X communications. KSII Trans Internet Inform Syst 7(8):1933–1953. doi: 10.3837/tiis.2013.08.011Ghafoor KZ (2013) Routing protocols in vehicular ad hoc networks: survey and research challenges, Netw Protocol Algorithm 5(4). doi: 10.5296/npa.v5i4.4134Ghafoor KZ, Bakar KA, Lloret J, Ke C-H, Lee KC (2013) Intelligent beaconless geographical routing for urban vehicular environments. Wirel Netw 19(3):345–362. doi: 10.1007/s11276-012-0470-zGhafoor KZ, Bakar KA, Lee K, AL-Hashimi H (2010) A novel delay- and reliability- aware inter-vehicle routing protocol. Netw Protocol Algorithms 2(2):66–88. doi: 10.5296/npa.v2i2.427Dias JAFF, Rodrigues JJPC, Isento JN, Pereira PRBA, Lloret J (2011) Performance assessment of fragmentation mechanisms for vehicular delay-tolerant networks. EURASIP J Wirel Commun Netw 2011(195):1–14. doi: 10.1186/1687-1499-2011-195Zhang D, Yang Z, Raychoudhury V, Chen Z, Lloret J (2013) An energy-efficient routing protocol using movement trend in vehicular Ad-hoc networks. Comput J 58(8):938–946. doi: 10.1093/comjnl/bxt028Ghafoor KZ, Lloret J, Bakar KA, Sadiq AS, Mussa SAB (2013) Beaconing approaches in vehicular Ad Hoc networks: a survey. Wirel Pers Commun. doi: 10.1007/s11277-013-1222-9Sadiq AS, Bakar KA, Ghafoor KZ, Lloret J (2013) An intelligent vertical handover scheme for audio and video streaming in heterogeneous vehicular networks. Mobile Netw Appl. doi: 10.1007/s11036-013-0465-8Khamayseh YM (2013) Network size estimation in VANETs. Netw Protocol Algorithm 5(3):136–152. doi: 10.5296/npa.v5i6.3838Rawat DB, Popescu DC, Yan G, Olariu S (2011) Enhancing VANET performance by joint adaptation of transmission power and contention window size. IEEE Trans Parallel Distrib Syst 22(9):1528–1535Yan G, Rawat DB, Bista BB. Provisioning vehicular ad hoc networks with quality of services. Int J Space-Based Situated Comput 2(2):104–111Rawat DB, Bista BB, Yan G, Weigle MC (2011) Securing vehicular ad-hoc networks against malicious drivers: a probabilistic approach, International Conference on Complex, Intelligent, and Software Intensive Systems Pp. 146–151. June 30, 2011Sun W, Xia F, Ma J, Fu T, Sun Y. An optimal ODAM-based broadcast algorithm for vehicular Ad-Hoc Networks. KSII Trans Internet Inform Syst 6(12): 3257–3274Vinel AV, Dudin AN, Andreev SD, Xia F (2010) Performance modeling methodology of emergency dissemination algorithms for vehicular ad-hoc networks, 6th Communication Systems, Networks & Digital Signal Processing (CSNDSP 2010), Pp. 397–400AL-Hashimi HN, Bakar KA, Ghafoor KZ (2010) Inter-domain proxy mobile IPv6 based vehicular network. Netw Protocol Algorithm 2(4):1–15. doi: 10.5296/npa.v2i4.488Ghafoor KZ, Bakar KA, Mohammed MA, Lloret J (2013) Vehicular cloud computing: trends and challenges, in the book “mobile computing over cloud: technologies, services, and applications”. IGI GlobalYan G, Rawat DB, Bista BB (2012) Towards secure vehicular clouds, Sixth International Conference on Complex, Intelligent and Software Intensive Systems (CISIS 2012), Pp. 370–375Fernández H, Rubio L, Reig J, Rodrigo-Peñarrocha VM, Valero A (2013) Path loss modeling for vehicular system performance and communication protocols evaluation. Mobile Netw Appl. doi: 10.1007/s11036-013-0463-xAllouche Y, Segal M (2013) A cluster-based beaconing approach in VANETs: near optimal topology via proximity information. Mobile Netw Appl. doi: 10.1007/s11036-013-0468-5Merah AF, Samarah S, Boukerche A, Mammeri A (2013) A sequential patterns data mining approach towards vehicular route prediction in VANETs. Mobile Netw Appl. doi: 10.1007/s11036-013-0459-6Zhang D, Huang H, Zhou J, Xia F, Chen Z (2013) Detecting hot road mobility of vehicular Ad Hoc Networks. Mobile Netw Appl. doi: 10.1007/s11036-013-0467-6El Ajaltouni H, Boukerche A, Mammeri A (2013) A multichannel QoS MAC with dynamic transmit opportunity for. Mobile Netw Appl. doi: 10.1007/s11036-013-0475-6Reñé S, Esparza O, Alins J, Mata-Díaz J, Muñoz JL (2013) VSPLIT: a cross-layer architecture for V2I TCP services over. Mobile Netw Appl. doi: 10.1007/s11036-013-0473-8Blanco B, Liberal F (2013) Amaia Aguirregoitia, application of cognitive techniques to adaptive routing for VANETs in city environments. Mobile Netw Appl. doi: 10.1007/s11036-013-0466-7Kim J, Krunz M (2013) Spectrum-aware beaconless geographical routing protocol for cognitive radio enabled vehicular networks. Mobile Netw Appl. doi: 10.1007/s11036-013-0476-5Dias JAFF, Rodrigues JJPC, Isento JNG, Niu J (2013) The impact of cooperative nodes on the performance of vehicular delay-tolerant networks. Mobile Netw Appl. doi: 10.1007/s11036-013-0464-9Sadiq AS, Bakar KA, Ghafoor KZ, Lloret J, Khokhar R (2013) An intelligent vertical handover scheme for audio and video streaming in heterogeneous vehicular networks. Mobile Netw Appl. doi: 10.1007/s11036-013-0465-8Machado S, Ozón J, González AJ, Ghafoor KZ (2013) Structured peer-to-peer real time video transmission over vehicular Ad Hoc networks. Mobile Netw Appl. doi: 10.1007/s11036-013-0461-zLin C, Wu G, Xia F, Yao L (2013) Enhance the attacking efficiency of the node compromise attack in vehicular Ad-hoc network using connected dominating set. Mobile Netw Appl. doi: 10.1007/s11036-013-0469-

An argument against the focus on Community Resilience in Public Health

Background - It has been suggested that Public Health professionals focus on community resilience in tackling chronic problems, such as poverty and deprivation; is this approach useful? Discussion - Resilience is always i) of something ii) to something iii) to an endpoint, as in i) a rubber ball, ii) to a blunt force, iii) to its original shape. “Community resilience” might be: of a neighbourhood, to a flu pandemic, with the endpoint, to return to normality. In these two examples, the endpoint is as-you-were. This is unsuitable for some examples of resilience. A child that is resilient to an abusive upbringing has an endpoint of living a happy life despite that upbringing: this is an as-you-should-be endpoint. Similarly, a chronically deprived community cannot have the endpoint of returning to chronic deprivation: so what is its endpoint? Roughly, it is an as-you-should-be endpoint: to provide an environment for inhabitants to live well. Thus resilient communities will be those that do this in the face of challenges. How can they be identified? One method uses statistical outliers, neighbourhoods that do better than would be expected on a range of outcomes given a range of stressors. This method tells us that a neighbourhood is resilient but not why it is. In response, a number of researchers have attributed characteristics to resilient communities; however, these generally fail to distinguish characteristics of a good community from those of a resilient one. Making this distinction is difficult and we have not seen it successfully done; more importantly, it is arguably unnecessary. There already exist approaches in Public Health to assessing and developing communities faced with chronic problems, typically tied to notions such as Social Capital. Communityresilience to chronic problems, if it makes sense at all, is likely to be a property that emerges from the various assets in a community such as human capital, built capital and natural capital. Summary - Public Health professionals working with deprived neighbourhoods would be better to focus on what neighbourhoods have or could develop as social capital for living well, rather than on the vague and tangential notion of community resilience.</p

A Novel RSSI Prediction Using Imperialist Competition Algorithm (ICA), Radial Basis Function (RBF) and Firefly Algorithm (FFA) in Wireless Networks

This study aims to design a vertical handover prediction method to minimize unnecessary handovers for a mobile node (MN) during the vertical handover process. This relies on a novel method for the prediction of a received signal strength indicator (RSSI) referred to as IRBF-FFA, which is designed by utilizing the imperialist competition algorithm (ICA) to train the radial basis function (RBF), and by hybridizing with the firefly algorithm (FFA) to predict the optimal solution. The prediction accuracy of the proposed IRBF–FFA model was validated by comparing it to support vector machines (SVMs) and multilayer perceptron (MLP) models. In order to assess the model’s performance, we measured the coefficient of determination (R2), correlation coefficient (r), root mean square error (RMSE) and mean absolute percentage error (MAPE). The achieved results indicate that the IRBF–FFA model provides more precise predictions compared to different ANNs, namely, support vector machines (SVMs) and multilayer perceptron (MLP). The performance of the proposed model is analyzed through simulated and real-time RSSI measurements. The results also suggest that the IRBF–FFA model can be applied as an efficient technique for the accurate prediction of vertical handover

Postnatal Pancreatic Islet β Cell Function and Insulin Sensitivity at Different Stages of Lifetime in Rats Born with Intrauterine Growth Retardation

Epidemiological studies have linked intrauterine growth retardation (IUGR) to the metabolic diseases, consisting of insulin resistance, type 2 diabetes, obesity and coronary artery disease, during adult life. To determine the internal relationship between IUGR and islet β cell function and insulin sensitivity, we established the IUGR model by maternal nutrition restriction during mid- to late-gestation. Glucose tolerance test and insulin tolerance test(ITT) in vivo and glucose stimulated insulin secretion(GSIS) test in vitro were performed at different stages in IUGR and normal groups. Body weight, pancreas weight and pancreas/body weight of IUGR rats were much lower than those in normal group before 3 weeks of age. While the growth of IUGR rats accelerated after 3 weeks, pancreas weight and pancreas/body weight remained lower till 15 weeks of age. In the newborns, the fasting glucose and insulin levels of IUGR rats were both lower than those of controls, whereas glucose levels at 120 and 180 min after glucose load were significantly higher in IUGR group. Between 3 and 15 weeks of age, both the fasting glucose and insulin levels were elevated and the glucose tolerance was impaired with time in IUGR rats. At age 15 weeks, the area under curve of insulin(AUCi) after glucose load in IUGR rats elevated markedly. Meanwhile, the stimulating index of islets in IUGR group during GSIS test at age 15 weeks was significantly lower than that of controls. ITT showed no significant difference in two groups before 7 weeks of age. However, in 15-week-old IUGR rats, there was a markedly blunted glycemic response to insulin load compared with normal group. These findings demonstrate that IUGR rats had both impaired pancreatic development and deteriorated glucose tolerance and insulin sensitivity, which would be the internal causes why they were prone to develop type 2 diabetes

Normal parameter reduction algorithm in soft set based on hybrid binary particle swarm and biogeography optimizer

© 2019, Springer-Verlag London Ltd., part of Springer Nature. Existing classification techniques that are proposed previously for eliminating data inconsistency could not achieve an efficient parameter reduction in soft set theory, which effects on the obtained decisions. Meanwhile, the computational cost made during combination generation process of soft sets could cause machine infinite state, which is known as nondeterministic polynomial time. The contributions of this study are mainly focused on minimizing choices costs through adjusting the original classifications by decision partition order and enhancing the probability of searching domain space using a developed Markov chain model. Furthermore, this study introduces an efficient soft set reduction-based binary particle swarm optimized by biogeography-based optimizer (SSR-BPSO-BBO) algorithm that generates an accurate decision for optimal and sub-optimal choices. The results show that the decision partition order technique is performing better in parameter reduction up to 50%, while other algorithms could not obtain high reduction rates in some scenarios. In terms of accuracy, the proposed SSR-BPSO-BBO algorithm outperforms the other optimization algorithms in achieving high accuracy percentage of a given soft dataset. On the other hand, the proposed Markov chain model could significantly represent the robustness of our parameter reduction technique in obtaining the optimal decision and minimizing the search domain.Published versio

Olprinone Attenuates the Acute Inflammatory Response and Apoptosis after Spinal Cord Trauma in Mice

BACKGROUND: Olprinone hydrochloride is a newly developed compound that selectively inhibits PDE type III and is characterized by several properties, including positive inotropic effects, peripheral vasodilatory effects, and a bronchodilator effect. In clinical settings, olprinone is commonly used to treat congestive cardiac failure, due to its inotropic and vasodilating effects. The mechanism of these cardiac effects is attributed to increased cellular concentrations of cAMP. The aim of the present study was to evaluate the pharmacological action of olprinone on the secondary damage in experimental spinal cord injury (SCI) in mice. METHODOLOGY/PRINCIPAL FINDINGS: Traumatic SCI is characterized by an immediate, irreversible loss of tissue at the lesion site, as well as a secondary expansion of tissue damage over time. Although secondary injury should be preventable, no effective treatment options currently exist for patients with SCI. Spinal cord trauma was induced in mice by the application of vascular clips (force of 24 g) to the dura via a four-level T5-T8 laminectomy. SCI in mice resulted in severe trauma characterized by edema, neutrophil infiltration, and production of inflammatory mediators, tissue damage, apoptosis, and locomotor disturbance. Olprinone treatment (0.2 mg/kg, i.p.) 1 and 6 h after the SCI significantly reduced: (1) the degree of spinal cord inflammation and tissue injury (histological score), (2) neutrophil infiltration (myeloperoxidase activity), (3) nitrotyrosine formation, (4) pro-inflammatory cytokines, (5) NF-kappaB expression, (6) p-ERK1/2 and p38 expression and (7) apoptosis (TUNEL staining, FAS ligand, Bax and Bcl-2 expression). Moreover, olprinone significantly ameliorated the recovery of hind-limb function (evaluated by motor recovery score). CONCLUSIONS/SIGNIFICANCE: Taken together, our results clearly demonstrate that olprinone treatment reduces the development of inflammation and tissue injury associated with spinal cord trauma